Jobs
Benefits and perks
•Remote Work
Required skills
Python
Machine Learning
Large Language Models
Multimodal Learning
Reinforcement Learning
PyTorch
TensorFlow
About the team
Zillow AI’s Foundational IQ group builds the core intelligence that powers search, discovery, and conversational experiences like Zillow Copilot. We combine text, imagery, geospatial and time‑series signals to learn rich representations of homes, neighborhoods, and shopper intent, then use them to improve user experiences on Zillow. Our team operates as applied researchers who ship: we prototype quickly, evaluate rigorously (offline metrics and online experiments), and partner closely with product and engineering to bring models to production. We care deeply about helpfulness, safety, and fairness, including domain‑specific, fair‑housing‑aware evaluation, and we invest in modern ML platforms, data governance, and observability to run at national scale. The result is AI that reduces friction, increases confidence, and makes complex home decisions feel simpler for millions of people.
About the role
As a PhD Research Intern on the Foundational IQ team, you will help train and adapt large models that better understand homes and users, advancing representation learning, multimodal modeling, user modeling, and reinforcement/sequential decision‑making for real‑world problems at Zillow scale. You’ll tailor and evaluate LLMs and multimodal foundation models to our domain, build agentic workflows that plan and act across multi‑step tasks, and define success via domain‑specific metrics emphasizing helpfulness, safety, and fairness. You’ll move quickly from prototype to impact, running rigorous offline evaluations and online experiments, collaborating with applied scientists, engineers, and product partners, and contributing to platform capabilities that power experiences like Zillow Copilot. Along the way you’ll author clear research docs, share results internally, and have opportunities to publish and present your work.
Responsibilities include:
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Research and develop methods for adapting LLMs and foundation models with Zillow’s domain-specific data
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Build and evaluate multimodal models that combine text, images, geospatial and tabular signals for home and user understanding.
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Explore reinforcement learning and sequential decision-making for long‑horizon, user‑centric outcomes
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Prototype agentic workflows; define success metrics and run rigorous offline/online evaluations
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Partner across science, engineering, product, and design; share results via docs, presentations, and publications
This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.
In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $104,000.00 - $166,000.00 annually. This base pay range is specific to these locations and may not be applicable to other locations.
In Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range for this role is $104,000.00 - $166,000.00 annually. The base pay range is specific to these locations and may not be applicable to other locations.
Who you are
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Currently enrolled in a PhD program in Computer Science, Machine Learning, Artificial Intelligence or a related field with a strong research track record
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Experience in one or more of the following:
LLMs: instruction tuning/fine‑tuning, prompting, and evaluation/measurement
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Multimodal learning (image + text; familiarity with audio or geospatial a plus)
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Representation learning with limited labels (self/semi/weakly-supervised)
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User modeling for personalization systems
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Reinforcement learning or sequential decision‑making
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Evaluating generative/agentic systems; privacy‑aware and responsible AI practices (e.g., fair‑housing considerations) are a plus
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Proficiency in Python and modern ML frameworks (e.g., Py Torch, Tensor Flow, Hugging Face)
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Clear communication and a collaborative mindset; motivated to publish at top venues
Here at Zillow - we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences.
Get to know us
At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help customers navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company that's reshaping an industry and helping more people make home a reality.
Zillow is honored to be recognized among the best workplaces in the country. Zillow was named one of FORTUNE 100 Best Companies to Work For® in 2025, and included on the PEOPLE Companies That Care® 2025 list, reflecting our commitment to creating an innovative, inclusive, and engaging culture where employees are empowered to grow.
No matter where you sit in the organization, your work will help drive innovation, support our customers, and move the industry—and your career—forward, together.
Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.
Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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About Zillow

Zillow
PublicZillow Group, Inc., or simply Zillow, is an American tech real-estate marketplace company that was founded in 2006 by co-executive chairmen Rich Barton and Lloyd Frink, former Microsoft executives and founders of Microsoft spin-off Expedia; Spencer Rascoff, a co-founder of Hotwire.com; David...
1,001-5,000
Employees
Seattle
Headquarters
$10.3B
Valuation
Reviews
3.7
10 reviews
Work-life balance
4.2
Compensation
3.8
Culture
3.5
Career
4.0
Management
2.5
65%
Recommend to a friend
Pros
Excellent benefits and compensation packages
Strong work culture and supportive environment
Good work-life balance and flexibility
Cons
Weak and dysfunctional management
Below-market pay in some areas
Aggressive quotas and pressure
Salary Ranges
26 data points
Junior/L3
L3
L4
L5
L6
Mid/L4
Senior/L5
Staff/L6
Director
Junior/L3 · DATA SCIENTIST I
1 reports
$153,949
total per year
Base
$118,414
Stock
-
Bonus
-
$153,949
$153,949
Interview experience
2 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Offer
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
Past Experience
Culture Fit
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